The enhancement of stability of p53 in MTBP induced p53–MDM2 regulatory network

We have modeled an MTBP-MDM2–p53 regulatory network by integrating p53–MDM2 autoregulatory model (Proctor and Gray, 2008) with the effect of a cellular protein MTBP (MDM2 binding protein) which is allowed to bind with MDM2 (Brady et al., 2005). We study this model to investigate the activation of p53 and MDM2 steady state levels induced by MTBP protein under different stress conditions. Our simulation results in three approaches namely deterministic, Chemical Langevin equation and stochastic simulation of Master equation show a clear transition from damped limit cycle oscillation to fixed point oscillation during a certain time period with constant stress condition in the cell. This transition is the signature of transition of p53 and MDM2 levels from activated state to stabilized steady state levels. We present various phase diagrams to show the transition between unstable and stable states of p53 and MDM2 concentration levels and also their possible relations among critical value of the parameters at which the respective protein level reach stable steady states. In the stochastic approach, the dynamics of the proteins become noise induced process depending on the system size. We found that this noise enhances the stability of the p53 steady state level.     

Stochastic Fluctuations and Distributed Control of Gene Expression Impact Cellular Memory

Despite the stochastic noise that characterizes all cellular processes the cells are able to maintain and transmit to their daughter cells the stable level of gene expression. In order to better understand this phenomenon, we investigated the temporal dynamics of gene expression variation using a double reporter gene model. We compared cell clones with transgenes coding for highly stable mRNA and fluorescent proteins with clones expressing destabilized mRNA-s and proteins. Both types of clones displayed strong heterogeneity of reporter gene expression levels. However, cells expressing stable gene products produced daughter cells with similar level of reporter proteins, while in cell clones with short mRNA and protein half-lives the epigenetic memory of the gene expression level was completely suppressed. Computer simulations also confirmed the role of mRNA and protein stability in the conservation of constant gene expression levels over several cell generations. These data indicate that the conservation of a stable phenotype in a cellular lineage may largely depend on the slow turnover of mRNA-s and proteins.     

The effect of natural selection on the propagation of protein expression noise to bacterial growth

In bacterial cells, protein expression is a highly stochastic process. Gene expression noise moreover propagates through the cell and adds to fluctuations in the cellular growth rate. A common intuition is that, due to their relatively high noise amplitudes, proteins with a low mean expression level are the most important drivers of fluctuations in physiological variables. In this work, we challenge this intuition by considering the effect of natural selection on noise propagation. Mathematically, the contribution of each protein species to the noise in the growth rate depends on two factors: the noise amplitude of the protein’s expression level, and the sensitivity of the growth rate to fluctuations in that protein’s concentration. We argue that natural selection, while shaping mean abundances to increase the mean growth rate, also affects cellular sensitivities. In the limit in which cells grow optimally fast, the growth rate becomes most sensitive to fluctuations in highly abundant proteins. This causes abundant proteins to overall contribute strongly to the noise in the growth rate, despite their low noise levels. We further explore this result in an experimental data set of protein abundances, and test key assumptions in an evolving, stochastic toy model of cellular growth.     

Stochastic models for circadian rhythms: effect of molecular noise on periodic and chaotic behaviour

Circadian rhythms are endogenous oscillations that occur with a period close to 24 h in nearly all living organisms. These rhythms originate from the negative autoregulation of gene expression. Deterministic models based on such genetic regulatory processes account for the occurrence of circadian rhythms in constant environmental conditions (e.g., constant darkness), for entrainment of these rhythms by light-dark cycles, and for their phase-shifting by light pulses. When the numbers of protein and mRNA molecules involved in the oscillations are small, as may occur in cellular conditions, it becomes necessary to resort to stochastic simulations to assess the influence of molecular noise on circadian oscillations. We address the effect of molecular noise by considering the stochastic version of a deterministic model previously proposed for circadian oscillations of the PER and TIM proteins and their mRNAs in Drosophila. The model is based on repression of the per and tim genes by a complex between the PER and TIM proteins. Numerical simulations of the stochastic version of the model are performed by means of the Gillespie method. The predictions of the stochastic approach compare well with those of the deterministic model with respect both to sustained oscillations of the limit cycle type and to the influence of the proximity from a bifurcation point beyond which the system evolves to stable steady state. Stochastic simulations indicate that robust circadian oscillations can emerge at the cellular level even when the maximum numbers of mRNA and protein molecules involved in the oscillations are of the order of only a few tens or hundreds. The stochastic model also reproduces the evolution to a strange attractor in conditions where the deterministic PER-TIM model admits chaotic behaviour. The difference between periodic oscillations of the limit cycle type and aperiodic oscillations (i.e. chaos) persists in the presence of molecular noise, as shown by means of Poincaré sections. The progressive obliteration of periodicity observed as the number of molecules decreases can thus be distinguished from the aperiodicity originating from chaotic dynamics. As long as the numbers of molecules involved in the oscillations remain sufficiently large (of the order of a few tens or hundreds, or more), stochastic models therefore provide good agreement with the predictions of the deterministic model for circadian rhythms.     

Expression of mRNAs of multidrug resistance proteins (Mrps) in cultured rat astrocytes,oligodendrocytes, microglial cells and neurones

Multidrug resistance proteins (Mrps) are ATP-driven export pumps that mediate the export of organic anions from cells. So far only little information is available on expression and physiological functions of Mrps in brain. The expression of mRNAs of six Mrp paralogs in rat brain, as well as in rat cultures enriched for neurones, astrocytes, oligodendrocytes and microglial cells, was studied by qualitative and semiquantitative RT-PCR analysis. In adult rat brain as well as in neural cell cultures the mRNAs coding for Mrp1, Mrp3, Mrp4 and Mrp5 were detected. Semiquantitative analysis revealed that the mRNAs coding for Mrp1 and Mrp5 were more abundant in the four cell culture types than mRNAs of the other Mrps. mRNAs coding for Mrp3 and Mrp4 were found at significant levels in cultured astrocytes and microglial cells, whereas cultures of neurones and oligodendrocytes contained only marginal quantities of these mRNAs. Putative physiological functions of Mrps in brain cells are discussed.     

Variability of the distribution of differentiation pathway choices regulated by a multipotent delayed stochastic switch

We study the plasticity of a delayed stochastic model of a genetic toggle switch as a multipotent differentiation pathway switch, at the single cell and cell population levels, by observing distributions of differentiation pathways choices of genetically homogeneous cell populations. Assuming a model of stochastic pathway determination of cell differentiation that is regulated by the proteins of the switch, we vary the proteins’ expression level and degradation rates, which cells are known to be able to regulate, to vary mean level, noise, and bias of the proteins’ expression levels. It is shown that small changes in each of these dynamical features significantly and distinctively affects the dynamics of the switch at the single cell level and thus, the cell differentiation patterns. The regulation of these features allows cells to regulate their pluripotency and cell populations’ distribution of lineage choice, suggesting that the stochastic switch has high plasticity regarding differentiation pathway choice regulation, thus providing adaptability to environmental stresses and changes.     

Ontogenesis of animals from the position of absence of self-maintaining synthesis of regulatory proteins]

The starting point of this paper is that there is no self-maintenance of most tissue-specific regulatory proteins. There in only one cycle within regulatory genes hierarchy--"germ line" cycle ensuring the next generation ontogeny. The consequences of this are stage-specificity of gene expression and organism ageing. To explain the existence of long-living differentiated cells, we assume that certain genes cause specific repression of mRNAs encoding regulatory proteins, thereby stabilizing the mRNAs. On the contrary, the mRNAs encoding regulatory proteins necessary for proliferation are to be translated due to growth factors. If one of the genes encoding such mRNAs acquires a foreign (viral, for example) promoter, the cell will divide infinitely; this can explain a number of nuclear proto-oncogenes properties. From this view-point, cell proliferation and differentiation, ontogeny and regeneration are considered.     

Context-dependent regulation of Musashi-mediated mRNA translation and cell cycle regulation.

Musashi-mediated mRNA translational control has been implicated in the promotion of physiological and pathological stem cell proliferation. During self-renewal of mammalian stem cells, Musashi has been proposed to act to repress the translation of mRNAs encoding inhibitors of cell cycle progression. By contrast, in maturing Xenopus oocytes Musashi activates translation of target mRNAs that encode proteins promoting cell cycle progression. The mechanisms directing Musashi to differentially control mRNA translation in mammalian stem cells and Xenopus oocytes is unknown. In this study, we demonstrate that the mechanisms defining Musashi function lie within the cellular context. Specifically, we show that murine Musashi acts as an activator of translation in maturing Xenopus oocytes while Xenopus Musashi functions as a repressor of target mRNA translation in mammalian cells. We further demonstrate that within the context of a primary mammalian neural stem/progenitor cell, Musashi can be converted from a repressor of mRNA translation to an activator of translation in response to extracellular stimuli. We present current models of Musashi-mediated mRNA translational control and discuss possible mechanisms for regulating Musashi function. An understanding of these mechanisms presents exciting possibilities for development of therapeutic targets to control physiological and pathological stem cell proliferation.     

Temporal resolution and sequential expression of muscle-specific genes revealed by in situ hybridization

The expression of muscle-specific mRNAs was analyzed directly within individual cells by in situ hybridization to chicken skeletal myoblasts undergoing differentiation in vitro. The probes detected mRNAs for sarcomeric myosin heavy chain (MHC) or the skeletal, cardiac, and beta isoforms of actin. Precise information as to the expression of these genes in individual cells was obtained and correlated directly with analyses of cell morphology and interactions, cell cycle stage, and immunofluorescence detection of the corresponding proteins. Results demonstrate that mRNAs for the two major muscle-specific proteins, myosin and actin, are not synchronously activated at the time of cell fusion. The mRNA for alpha-cardiac actin (CAct), known to be the predominant embryonic actin isoform in muscle, is expressed prior to cell fusion and prior to the expression of any isoform of muscle MHC mRNA. MHC mRNA accumulates rapidly immediately after fusion, whereas skeletal actin mRNA is expressed only in larger myofibers. Single cells expressing CAct mRNA have a characteristic short bipolar morphology, are in terminal G1, and do not contain detectable levels of the corresponding protein. In a pattern of expression reciprocal to that of CAct mRNA, beta-actin mRNA diminishes to low or undetectable levels in myofibers and in cells of the morphotype which expresses CAct mRNA. Finally, the intracellular distribution of mRNAs for different actin isoforms was compared using nonisotopic detection of isoform-specific oligonucleotide probes. This work illustrates a generally valuable approach to the analysis of cell differentiation and gene expression which directly integrates molecular, morphological, biochemical, and cell cycle information on individual cells.